Aims: We aimed at assessing the feasibility of 24-hour ECG/SCG monitoring and analysis in a real-world setting by proposing a novel method based on labelling for quality each beat on the SCG, and then extracting parameters relevant to cardiac electro-mechanical activity, with the evaluation of their circadianity.
Methods: Twenty-two healthy volunteers (15 F and 7 M; age: median [25th;75th] 29.5[25;54.8] years; BMI: 23.3[21.1;24.5] Kg/m2) were recruited. A commercial wearable device (EcgMove4, Movisens Gmbh) was worn for 24 hours, simultaneously acquiring 1-lead ECG (1024 Hz), and 6-axis SCG (64 Hz). Signal preprocessing to remove noise and respiratory motion artifacts was applied on the dorso-ventral linear acceleration component. An innovative ECG-dependent approach that combines signal's morphology and known physiological information was developed to identify analyzable heartbeats on the SCG signals over the 24-hours and to extract relevant fiducial points, such as aortic valve opening (AO), isovolumetric contraction (IVC) and aortic valve closure, from which left ventricular ejection time, and contractility-related parameters (delta amplitude and slope between AO and IVC) were computed. Their circadianity was assessed by Cosinor analysis, with day-night differences evaluated through statistical analysis (Wilcoxon Signed Rank).
Results: Our findings demonstrate the feasibility of 24-hour ECG/SCG analysis for cardiac electro-mechanical parameters, despite the low sampling frequency of the SCG. A higher feasibility was obtained during night-time (82[70;90]%) compared to the day (49.9 [40;52]%), but reliable enough to provide a day-night difference in all the considered parameters as well as the circadianity in both temporal and contractility-related parameters.
Conclusion: Our work shows the feasibility of 24-hour combined ECG/SCG automated analysis for extracting electro-mechanical activity parameters and evaluating their circadian variations, extending the potential of a commercially available device in which inertial measures are conventionally used for postural analysis. Highlighted day-night differences represent normality ranges to which comparing future data from patients.